Senior ML Platform & Ops Engineer - Hybrid Madrid

Preply; Madrid; Híbrido; EUR 90.000 - 120.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Lessons allowance

Learning & Development budget

Equity

Health insurance

Descripción de la vacante

Preply is seeking a Senior Machine Learning Platform/Ops Engineer to build and maintain ML pipelines and scalable ML infrastructure in Madrid, Spain. You will collaborate with ML Scientists to deploy reproducible training environments, manage compute at scale, and implement observability for production systems.

The role requires hands-on experience in Python/SQL, orchestration tools, cloud platforms (GCP/AWS), Kubernetes, and modern DevOps practices.

Formación

• Proven experience designing and deploying ML systems in production (5+ years)
• Proficiency in Python and SQL, and orchestration tools (Airflow, Kubeflow, Dagster)
• Experience with modern cloud platforms (GCP/AWS) and Kubernetes
• Understanding of ML model lifecycles: training, validation, deployment, monitoring
• Strong DevOps practices: Git, IaC (Terraform), logging/observability, containerization (Docker/K8s)

Responsabilidades

• Build and maintain ML pipelines for training, evaluation, and deployment
• Support AI scientists with reproducible training environments and scale compute
• Define observability and alerting for ML systems (model drift, data quality)
• Design and scale data ingestion and feature transformation flows (batch and streaming)
• Contribute to internal Python libraries and platform tooling for model teams
• Ensure ML services are modular, testable, and monitored from day one
• Explore and productionize LLM-based features (retrieval pipelines, model serving)

Conocimientos

Python

SQL

Airflow

Kubeflow

Dagster

Terraform

Docker

Kubernetes

CI/CD

Git

IaC

Cloud platforms (GCP/AWS)

LLM serving

Vector databases

Herramientas

Databricks

MLFlow

Airflow

Descripción del empleo

Preply is seeking a Senior Machine Learning Platform/Ops Engineer to build and maintain ML pipelines and scalable ML infrastructure in Madrid, Spain. You will collaborate with ML Scientists to deploy reproducible training environments, manage compute at scale, and implement observability for production systems.

The role requires hands-on experience in Python/SQL, orchestration tools, cloud platforms (GCP/AWS), Kubernetes, and modern DevOps practices.